Project Summary/Abstract The recognition that patients suffering from the same disease may manifest its pathophysiology or respond to therapy disparately has focused attention on the goal of personalized medicine. This theme is particularly relevant to cancer where heterogeneity amongst patients is matched by the emerging issue of intratumor heterogeneity. Genetic sequencing and lineage-tracing studies now support that heterogeneity within tumors is attributable to both evolving genetic subclones and to the diverse developmental states that support tumor growth. Although less well studied from the standpoint of heterogeneity, cancer cells undergo complex but incompletely elucidated reprogramming of glucose, amino acid, and fatty acid metabolic pathways to support growth and proliferation. Metabolic imaging studies at gross tissue resolution suggest that tumor metabolism also exhibits heterogeneity. Yet despite the generally accepted existence of tumor heterogeneity, fundamental knowledge gaps remain, including the critical question of what aspects of tumor heterogeneity affect prognosis and treatment responsiveness? An equally important question is what technologies can obtain clinically useful information about tumor heterogeneity? In representing the downstream functional integration of genetic, epigenetic and microenvironmental regulatory networks, I hypothesize that the metabolic adaptations engaged to promote survival and growth are critical indicators of cancer cell function and therefore directly relevant to disease progression and therapeutic response. Furthermore, I propose that a new imaging technology, multi- isotope imaging mass spectrometry (MIMS), is ideally suited to obtain clinically useful information about tumor heterogeneity. MIMS is a state-of-the-art quantitative metabolic imaging technology with subcellular resolution, pioneered at the Brigham and Women's Hospital over the past decade. In coupling high-resolution ion microscopy with stable isotope tracer methodology, MIMS functionally illuminates subcellular domains much smaller than a cubic micron. I now propose MIMS as a new tool for studying cancer metabolism in humans at the single cell level, with the ultimate goal of dramatically refining the pathologic diagnosis and grading of human tumor specimens in a way that supports the goal of precision cancer therapy. To further this vision, I will rigorously explore the functional significance of tumor metabolic heterogeneity with two inter-related studies: First, I will utilize robust murine cancer models of targeted therapy and resistance to test the hypothesis that MIMS measurements at the single cell level can identify metabolically distinct, and therapeutically resistant, tumor cell subpopulations. Second, I will perform a translational first-in-human MIMS study to test the hypothesis that heterogeneity in glucose and glutamine metabolism exists in the tumors of human cancer patients and that treatment selects for metabolically distinct cells. Completion of these studies will break new ground in the understanding of how metabolic adaptations of tumor cells aid survival and proliferation, while validating an entirely new approach to studying human tumors.